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An Autoregressive Repeatability Animal Model for Test-Day Records in Multiple Lactations

J. Carvalheira^*,, E. J. Pollak, R. L. Quaas and R. W. Blake

^* Instituto de Ciências Biomédicas Abel Salazar and
Centro de Estudos de Ciência Animal, Universidade do Porto, Rua do Monte-Crasto, 4485-661 Vairão, Portugal
Department of Animal Science, Cornell University, Ithaca, NY 14853

Corresponding author:
J. Carvalheira; e-mail:
jgc3{at}mail.icav.up.pt.

Test-day (TD) models are becoming a standard for genetic evaluation of production traits in dairy cattle. Various approaches to model covariances between TD records include random regression, autoregressive repeatability, orthogonal polynomials, and models based on character processing. The applicability of these models is mainly associated with the number of parameters to estimate, incorporation of multiple lactations, and the accuracy of correlations generated by the cow’s repeated expression of milking performance (TD yields) within and across lactations. We define and evaluate a multiple-lactation, autoregressive-repeatability model that disentangles environmental effects due to cow within and between lactations. Simulated records either included or ignored a long-term environmental effect between lactations. Our autoregressive TD animal model correctly detected presence and the absence of this effect and accurately recovered the assumed variance components and correlations underlying the data (10 parameters for three lactations). Estimates of variance components and autocorrelation coefficients were obtained using DFREML-simplex methodology. Given the value of this approach to reduce the size of residual variance components, autoregressive animal models are a preferable alternative to classical methods based on cumulative lactation yield to improve milk production in dairy cattle.

Abbreviation key: CL = confidence limit, HTD = herd-test-date, LTE = long-term environmental effect, STE = short-term environmental effect, TD = test day

Key Words: test-day animal model • dairy cattle • autoregression • genetic evaluation

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